class_docstr: Wrapper for evaluating a :mod:`torchvision:torchvision.models` model on
  images.
  
  Args:
      config: an :class:`TorchvisionImageModelConfig`
class_docstr_tok: ["Wrapper","for","evaluating","a",":","mod",":","`","torchvision",":","torchvision.models","`","model","on","images",".","Args",":","config",":","an",":","class",":","`","TorchvisionImageModelConfig","`"]
code: def _load_model(self, config):
      if config.entrypoint_args:
          # pretrained=True was used instead of weights in torchvision < 0.13
          if version.parse(torchvision.__version__) < version.parse(
              "0.13.0"
          ):
              weights = config.entrypoint_args.pop("weights", None)
              if weights is not None:
                  config.entrypoint_args["pretrained"] = True
  
      ctx = contextlib.nullcontext()
      if config.entrypoint_fcn is not None:
          try:
              ctx = _make_load_state_dict_from_url_monkey_patcher(
                  config.entrypoint_fcn, fo.config.model_zoo_dir
              )
          except Exception as e:
              logger.warning(
                  "Failed to monkey patch load_state_dict_from_url(): %s",
                  e,
              )
  
      with ctx:
          return super()._load_model(config)
  
file_path: fiftyone/fiftyone/zoo/models/torch.py
imports: import contextlib
  import inspect
  import logging
  from packaging import version
  import fiftyone
  import fiftyone.core.utils
  import fiftyone.utils.torch
  import fiftyone.zoo.models
  import torchvision
label_desc: Use image node_id 2 for calling the TorchvisionImageModel obj's underlying member method code with example usage: obj._load_model(config) and returns: super